Data Sources

Sohail Khan

Senior Data Science Fellow 2025-2026, Data Science Fellow 2024-2025
School of Information

Hey everyone, I’m Sohail - a 1st years Master’s student studying Data Science at the I-School. I am interested in the intersection between Computer Science, Data Science, and Cognitive Psychology and using these tools to understand, discover, and drive the development of assistive technologies.

I have experience building with brain computer Interfaces, developing distributed data processing applications, and am currently working on a large scale archival project aimed at preserving the history and memory of resistance movements through an embedding based...

Scarlet Sands-Bliss

Data Science & AI Fellow 2025-2026, Domain Consultant, Research IT
School of Public Health

Scarlet Bliss is an MS/PhD student in Epidemiology in the School of Public Health. Her work focuses on mixed methods approaches to characterizing and preventing spread of antimicrobial resistance and other enteric pathogens via the environment. She has experience in statistical analysis and public health bioinformatics. She is interested in ethical use of big data as it relates to epidemiologic research.

Jose Aguilar

Data Science & AI Fellow 2025-2026
Berkeley Graduate School of Education

Jose R. Aguilar is currently a PhD student in the Policy, Politics, and Leadership program at UC Berkeley’s School of Education. His research utilizes natural language processing, machine learning, and social network analysis to investigate how institutional discourse, algorithmic decision-making, and education policy influence postsecondary access and equity for marginalized students. Before Berkeley, Jose earned his M.A. in Urban Education from Loyola Marymount University and dual B.A./B.S.A. degrees in Government, Latina/o Studies, and Computer Science from the University of...

Sarah Daniel

Data Science & AI Fellow 2025-2026
Political Science

Sarah Daniel is a PhD candidate in Political Science, specializing in urban politics in Sub-Saharan Africa, with a particular focus on East Africa. Her research examines how neighborhood communities organize for collective action to improve service delivery, reduce inequality, and enhance political representation.

Armaan Hiranandani

Data Science & AI Fellow 2025-2026
School of Information

Armaan Hiranandani is a Master’s student in Data Science at UC Berkeley, where he also earned his B.S. in Industrial Engineering & Operations Research. Born and raised in Dubai, Armaan recently completed a software engineering internship at Netflix, working on the machine learning platform team. His interests include building scalable AI systems and applying data science to solve real-world problems.

Paige Park

Data Science & AI Fellow 2025-2026
Demography

Paige Park is a Doctoral candidate in Demography. Her dissertation investigates applications of AI to demography, including deep learning based demographic forecasting. She is interested in using emerging tools to better model and contextually understand mortality, fertility, and migration patterns, particularly in the US context. She received an MA in Statistics from UC Berkeley in 2023.

Maksymilian Jasiak

Data Science & AI Fellow 2025-2026
Civil and Enviromental Engineering

Maksymilian Jasiak is a PhD Student in GeoSystems Engineering at the University of California, Berkeley. His research focuses on Distributed Fiber Optic Sensing (DFOS) for lifeline infrastructure monitoring. His work aims to advance critical infrastructure security and resilience. He holds a Master of Science in GeoSystems Engineering from the University of California, Berkeley and a Bachelor of Science in Civil Engineering from the University of Illinois Urbana-Champaign.

Decision-Making Under Pressure during My PhD: Lessons from whale songs and ocean noise

May 6, 2025
by Jaewon Saw. This blog post shares a story from a field experiment using Distributed Acoustic Sensing (DAS) to detect whale vocalizations in Monterey Bay. Most of the data got overwhelmed by noise from boat engines, wave motion, and cable instability. On the final day, a spur-of-the-moment decision to add loops to the fiber optic cable dramatically improved signal quality.

Predicting the Future: Harnessing the Power of Probabilistic Judgements Through Forecasting Tournaments

April 29, 2025
by Christian Caballero. From the threat of nuclear war to rogue superintelligent AI to future pandemics and climate catastrophes, the world faces risks that are both urgent and deeply uncertain. These risks are where traditional data-driven models fall short—there’s often no historical precedent, no baseline data, and no clear way to simulate a future world. In cases like this, how can we anticipate the future? Forecasting tournaments offer one answer, harnessing the wisdom of crowds to generate probabilistic estimates of uncertain future events. By incentivizing accuracy through structured competition and deliberation, these tournaments have produced aggregate predictions of future events that outperform well-calibrated statistical models and teams of experts. As they continue to develop and expand into more domains, they also raise urgent questions about bias, access, and whose knowledge gets to shape our collective sensemaking of the future.

Frances Leung

Data Science Fellow 2021-2022
School of Information

Frances Leung is a master’s student at UC Berkeley School of Information where she focuses her studies in information and data science. She has a keen interest in leveraging data-driven insights to better understand consumer behaviors and the world around us. In her professional work as a management consultant, she advises retailers and consumer businesses on digital transformation and creating web/mobile experiences that delight consumers through a human-centered approach. Frances holds a Master in Business Administration from York University, Schulich School...